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A Risk Model with Renewal Shot-Noise Cox Process
id: 2262
Date: 20161019
status: published
Times:
Magazines
65,55-65, 2015
Author
Angelos Dassios, Hongbiao Zhao
Content
In this paper we generalise the risk models beyond the ordinary framework of affine processes or Markov processes and study a risk process where the claim arrivals are driven by a Cox process with renewal shot-noise intensity. The upper bounds of the finite-horizon and infinite-horizon ruin probabilities are investigated and an efficient and exact Monte Carlo simulation algorithm for this new process is developed. A more efficient estimation method for the infinite-horizon ruin probability based on importance sampling via a suitable change of probability measure is also provided; illustrative numerical examples are also provided.
JEL-Codes
G22; C10; C60
Keywords
Risk model; Ruin probability; Renewal shot-noise Cox process; Piecewise-deterministic Markov process; Martingale method; Importance sampling; Change of probability measure; Rare-event simulation
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